(Montana State University, 2017-04) Grudzien, Maia
As infrastructure is rebuilt, or as new roads are being designed, safety should be at a top priority. This project has been looking at understanding accident prone areas in a particular region, such as Montana, as well as larger cities like Seattle. As crash data was collected, maps were generated from the data and then layers were applied. Layers, or sorting factors, could include population density, clusters, city regions (i.e. sporting event complexes, shopping centers), etc. The goal of this project is to provide examples to engineers and city planners of safe and accident-prone roads and intersections, and in the long term, these data sets will be used to create better network comparison algorithms.
